Upload README.md

README.md

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----
-license: apache-2.0
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+# Robot Control Dataset
+
+## Overview
+
+The TD-NIRS and EEG data for this dataset was collected using a Kernel Flow headset.
+
+Participants were asked to:
+- Clench left fist
+- Clench right fist
+- Clench both fists
+- Tap tongue
+- Relax
+
+## Data
+
+The `data` folder contains numpy files. Each numpy file represents a 15s chunk of data.
+
+### Timing
+
+```
+t=0             t=3                     t=15
+rest period     stimulus presented      end of data
+```
+
+### Format
+
+You can use the following to load a chunk:
+```python
+arr = np.load('/tmp/file.npz', allow_pickle=True)
+```
+
+There are 3 keys in this array:
+```python
+> list(arr.keys())
+
+['feature_moments', 'feature_eeg', 'label']
+```
+
+### Labels
+
+You can access the label with:
+```python
+> arr['label'].item()
+
+{'label': 'Both Fists',
+ 'subject_id': None,
+ 'session_id': 'bf56a42cfa7e4026be1b1ecdb130d3b3',
+ 'duration': 9.411478996276855}
+```
+
+The labels are:
+- `Right Fist`
+- `Left First`
+- `Both Firsts`
+- `Tongue Tapping`
+- `Relax`
+
+The `subject_id` represents a unique participant. Chunks with the same `subject_id` came from the same participant.
+
+The `session_id` represents a unique ID for the recording. Chunks with the same `session_id` came from the same recording.
+
+The `duration` is the duration of the stimulus itself. The cue was presented at t=3 in the chunk and was removed `duration` seconds after. The participant was in a rest state for the rest of the chunk.
+
+## EEG
+
+You can access the EEG data with:
+```python
+> arr['feature_eeg'].shape
+
+(7499, 6) # (num_samples, num_channels)
+```
+
+The first dimension has the samples. The EEG streams at 500Hz and 15 seconds at 500Hz is 7499 samples.
+
+The second dimension corresponds to the 6 channels. Their locations are:
+```
+0     1     2     3     4    5
+AFF6  AFp2  AFp1  AFF5  FCz  CPz
+```
+
+## TD-NIRS
+
+You can access the TD-NIRS data with:
+```python
+> arr['feature_moments'].shape
+
+(72, 40, 3, 2, 3) # (num_samples, num_modules, num_sds_ranges, num_wavelengths, num_moments)
+```
+
+The first dimension has the samples. The TD-NIRS streams at 4.76Hz and 15 seconds at 4.76Hz is 72 samples.
+
+The second dimension corresponds to the 40 modules on the Kernel Flow headset. The moments data is averaged by module across channels where the module acted as a source.
+
+The third dimension corresponds to the 3 various SDSs (source-detector separations) used. The moments data is averaged across channels whose separation is within a range. The mapping to index is:
+```
+0: short channels from 0mm to 10mm
+1: medium channels from 10mm to 25mm
+2: long channels from 25mm to 60mm
+```
+
+The fourth dimension corresponds to the wavelengths in the Kernel Flow system. Each sample contains 2 wavelengths worth of data:
+```
+0: 690nm / red
+1: 905nm / infrared
+```
+
+The fifth dimension corresponds to the 3 moments:
+```
+0: log10(sum) - logarithm of total intensity
+1: mean time of flight - average arrival time of photons
+2: variance/central moment - temporal broadening of the photon pulse
+```